Lecture 9: Negotiation

MIT OpenCourseWare · Intermediate ·🤖 AI Agents & Automation ·2mo ago

Key Takeaways

Explores negotiation as an application of backward induction in game theory

Original Description

MIT 14.12 Economic Applications of Game Theory, Fall 2025 Instructor: Ian Ball View the complete course: https://ocw.mit.edu/courses/14-12-economic-applications-of-game-theory-fall-2025/ YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63quuKvMHCt3cmTmt0O2qpv In this lecture, Ian Ball explores negotiation, an application of backward induction. He uses two examples: pre-trial hearing settlements, and price haggling. License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu Support OCW at http://ow.ly/a1If50zVRlQ We encourage constructive comments and discussion on OCW’s YouTube and other social media channels. Personal attacks, hate speech, trolling, and inappropriate comments are not allowed and may be removed. More details at https://ocw.mit.edu/comments.
Watch on YouTube ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related Reads

📰
Bitemporal AI Memory: How to Preserve What an Agent Knew Then
Learn how bitemporal AI memory preserves an agent's past knowledge, improving its decision-making capabilities
Dev.to · Ethan Beirne
📰
I run my one-person business with 12 AI employees. Here's the actual org chart.
Learn how to leverage AI employees to streamline a one-person business, increasing productivity and efficiency
Dev.to · Luna
📰
Why Agentic AI Needs More Than Standard Model Risk Management
Agentic AI requires more than standard model risk management due to its dynamic nature, learn why and how to adapt
Medium · AI
📰
What is Anyscale? The Platform Powering Scalable AI and Python Applications
Learn about Anyscale, a platform for scalable AI and Python applications, and how it simplifies development, scaling, and operations for AI teams
Medium · Startup
Up next
What is AI Agents Swarm Explained with Examples
VLR Software Training
Watch →